Justin Gottschlich

Head of Machine Programming Research, Intel Labs

Chair of Industrial Board and Executive Director at PRECISE, University of Pennsylvania

Steering Committee Chair, ACM SIGPLAN Machine Learning and Programming Languages Workshop

Principal Investigator and Co-Founder, Intel/NSF CAPA Research Center

Adjunct Assistant Professor, University of Pennsylvania


Maaz Ahmad (advised by Alvin Cheung @ Berkeley)

Akhilesh Gupta (advised by Insup Lee @ Penn)

Roshni Iyer (advised by Yizhou Sun and Wei Wang @ UCLA)

Ramneet Kaur (advised by Insup Lee @ Penn)

Fangke Ye (advised by Vivek Sarkar @ Georgia Tech)

PanteA Zardoshti (advised by Mike Spear @ Lehigh)


NeurIPS'20, MAPL'20 (SC chair), aiDM '20, TheWebConf'20, MLSys'20, PACT'19 (SRC), SysML'19, MAPL'18 (general chair), MAPL'17 (PC chair)


MAPL 2020 paper deadline has been updated to March 31!

Our research has been highlight by the New York Times, SDTimes, Economic Times, Venturebeat, and Wharton, to name a few.

Keynote @ PRECISE's Industry Day: "Machine Programming: The Future of Autonomy"

AutoPerf (NeurIPS'19) has been open sourced.

Intel Newsroom Press Release on my team's Machine Programming Research.

Contact: justin.gottschlich@intel.com


I founded and lead the Machine Programming Research group at Intel Labs. The field of machine programming (MP) is concerned with automating the development of software and – as a byproduct – hardware. MP is a fusion of many fields. These include, but are not limited to, machine learning, programming languages, software engineering, compilers, systems, and formal methods. We provide a brief overview of MP in our “Three Pillars of Machine Programming” vision paper (see Armando Solar-Lezama's website for a deeper dive).

In addition to my roles at Intel, I'm the principal investigator and co-founder of the joint Intel/NSF CAPA research center and I work closely with several universities. In particular, I'm adjunct faculty at University of Pennsylvania (Penn) and am the chair of the industrial board and executive director of the PRECISE Center at Penn. In 2016, I co-founded the Machine Learning and Programming Languages (MAPL) workshop. After taking on the roles of both program chair (2017) and general chair (2018), I accepted an invitation by the steering committee (SC) to become the SC chair. When not doing research, I occasionally work on my online gaming software company, Nodeka, LLC, which I've been running since 1999.

I have ~70 peer reviewed publications and issued patents with ~80 patents pending. I've given several dozen research talks at places like Berkeley, BMW, IBM, Intel, Penn, Stanford, UCLA, UW, VMWare, and Wharton. My (somewhat dated) CV is here.


Patent issued: "Detecting Mobile Device Sensor Malfunctions" (10,591,313)

SDTimes & Economic Times highlighting our research.

Patent issued: "Extend GPU/CPU coherency to multi-GPU cores" (10,521,349)

Venturebeat has published an article on my team's machine programming research @ NeurIPS '19!

Patent issued: "Efficient sharing and compression expansion of data across processing systems" (10,497,084)

Interview with Knowledge@Wharton on machine programming.

Open source: AutoPerf (NeurIPS'19) has been released to the open source community.

Patent issued: "Methods and systems for performing a replay execution" (10,474,471)

Intel Newsroom Press Release on my team's Machine Programming Research.

Intel Division Recognition Award: "Outstanding Leadership of Machine Programming Patent Harvest"

Patent issued: "Compute optimization mechanism for deep neural networks" (10,417,734)

Patent issued: "Compute optimization mechanism for deep neural networks" (10,417,731)

Patent issued: "Autonomous machines through cloud, error corrections, and predictions" (10,410,115)

Accepted to NeurIPS: "A Zero-Positive Learning Approach for Diagnosing Software Performance Regressions"

Opening address for Machine Programming Day @ Berkeley: "Intel's Machine Programming Pioneering Research Vision"

Patent issued: "Mechanism for facilitating dynamic and efficient management of instruction atomicity violations in software programs at computing systems"

Patent issued: "Methods and systems to identify and reproduce concurrency violations in multi-threaded programs using expressions"

Accepted invitation as chair of MAPL steering committee.

Q2 Intel Labs' Eureka Award Winner (inventor with most patent applications filed in a quarter (30 new filings)).

Accepted invitation to serve on SysML 2020 program committee.

Patent issued: "Autonomous vehicle advanced sensing and response"

Intel Tech Insights Leadership Award: "Machine Programming: A Radical Approach to Automating Software" (Justin Gottschlich and Tim Mattson)

Patent issued: "Coordination and increased utilization of graphics processors during inference"

Patent issued: "Extend GPU/CPU coherency to multi-GPU cores"

DATSA has been open sourced.

SysML whitepaper: "SysML: The New Frontier of Machine Learning Systems"

Invited talk, Stanford DAWN Retreat '19: "Machine Programming"


PhD co-advisor: Irina Calciu, Brown University - VMWare

PhD committee member: Wenjia Ruan, Lehigh University - Qualcomm

PhD committee member: Mohammad Mejbah ul Alam - Intel Labs